Results 251 to 260 of about 3,008,864 (289)
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IEEE Congress on Evolutionary Computation, 2010
FluidDB is a new structured storage system, available online for limited alpha test, which is designed to be able to easily store objects and relations among them (using tags). It is accessible through a simple REST interface, which is usually wrapped in a high-level language library.
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FluidDB is a new structured storage system, available online for limited alpha test, which is designed to be able to easily store objects and relations among them (using tags). It is accessible through a simple REST interface, which is usually wrapped in a high-level language library.
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Integrated Evolutionary Algorithms
2002The role of sex in evolutionary algorithms, difference between gene and meme are presented. The role of Darwinian selection process, Mendelians genetics, Lamarckian inheritance, Baldwin effect and Dawkins theory of memes are discussed. All states of integrated evolution can be stored in four memories.
Pavel Osmera, Jan Roupec
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Factored Evolutionary Algorithms
IEEE Transactions on Evolutionary Computation, 2017Factored evolutionary algorithms (FEAs) are a new class of evolutionary search-based optimization algorithms that have successfully been applied to various problems, such as training neural networks and performing abductive inference in graphical models.
Shane Strasser +3 more
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Analyses of evolutionary algorithms
2009Evolutionäre Algorithmen (EAs) werden in der Praxis sehr erfolgreich eingesetzt. Bisher werden die theoretischen Grundlagen von EAs jedoch nicht zufriedenstellend verstanden. Laufzeitanalysen für einfache EAs sollen dieses Verständnis erweitern.
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Evolving evolutionary algorithms
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation, 2012This paper proposes a Grammatical Evolution framework to the automatic design of Evolutionary Algorithms. We define a grammar that has the ability to combine components regularly appearing in existing evolutionary algorithms, aiming to achieve novel and fully functional optimization methods. The problem of the Royal Road Functions is used to assess the
Nuno Lourenço 0002 +2 more
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Parallel evolutionary algorithms
Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694), 2004We are trying to piece together the knowledge of evolution with the help of biology, informatics and physics to create a complex evolutionary structure. It can speed up the creation of optimization algorithms with high quality features. The adaptive significance of GAs with sexual reproduction and an artificial immune system is presented. An artificial
Pavel Osmera +2 more
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A Destructive Evolutionary Algorithm Process
2007 Frontiers in the Convergence of Bioscience and Information Technologies, 2007This paper describes the application of evolutionary search to the problem of Flash memory wear-out. The current method for establishing memory operating parameters is a time consuming and expensive manual process of destructive testing. Understandably this process is normally undertaken only at design time.
Joe Sullivan, Conor Ryan
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Herding Evolutionary Algorithm
Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015In this paper, we address the problem of black box optimization over binary vectors. We introduce a novel evolutionary algorithm called Herding Evolutionary Algorithm which relies on herding to generate individuals with empirical moments close to those of selected individuals. We report experiments with diverse fitness functions and compare the results
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Bull. EATCS, 1999
Summary: We discuss the paradigm of Evolutionary Algorithms (EAs). We argue about the need for new heuristics in real-world solving, compare the evolutionary approach to local search, simulated annealing, and tabu search, and indicate the potential behind the evolutionary approach.
David B. Fogel, Zbigniew Michalewicz
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Summary: We discuss the paradigm of Evolutionary Algorithms (EAs). We argue about the need for new heuristics in real-world solving, compare the evolutionary approach to local search, simulated annealing, and tabu search, and indicate the potential behind the evolutionary approach.
David B. Fogel, Zbigniew Michalewicz
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What is an Evolutionary Algorithm?
2003The most important aim of this chapter is to describe what an evolutionary algorithm is. This description is deliberately based on a unifying view presenting a general scheme that forms the common basis of all evolutionary algorithm (EA) variants. The main components of EAs are discussed, explaining their role and related issues of terminology. This is
A. E. Eiben, J. E. Smith
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